1. Field of the Invention
The present invention relates to a machine learning apparatus, a motor drive apparatus, a motor drive system, and a machine learning method, and specifically relates to a machine learning apparatus for learning a filter in accordance with a machine command, a motor drive apparatus and a motor drive system having the machine learning apparatus, and a machine learning method.
2. Description of Related Art
In motor drive apparatuses, analog signals are sometimes used in a circuit for detecting an electric current supplied to a motor and a circuit for feeding back the position of the motor. When noise is applied to the analog signal, the precision of an entire system is affected. Thus, the analog signal is subjected to a filter in order to remove the noise and eliminate the adverse effect on the precision of the entire system (for example, Japanese Unexamined Patent Publication (Kokai) No. 2012-062044, hereinafter called “patent document 1”).
The patent document 1 discloses a communication control system that is applied to vehicles equipped with various devices that could be noise sources, to select a wireless communication method associated with the vehicle. The communication control system includes a detection means for detecting operation states of the various devices that become noise sources, an estimation means for estimating electromagnetic noise characteristics specific to the operation states based on the operation states of the various devices detected by the detection means, and a selection means for selecting a communication method in accordance with the electromagnetic noise characteristics estimated by the estimation means. This configuration allows for selecting the suitable communication method for the operation states of the various devices that become noise sources e.g. the rotating state of a motor in the vehicle, thus facilitating the establishment of good communication.
The larger the filter applied to the analog signal, the more noise is removed. However, too large of a filter degrades responsivity and loses immediacy. Also, since the amount and component of noise varies depending on the state of a system or a machine, an optimal filter is not constant, and thus a fixed filter is not always optimal.